Netflix Tech

NOVEMBER 12, 2024

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.

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Datasets Computer Science Systems Kafka 89

Lyft Engineering

APRIL 25, 2023

Building a large scale unsupervised model anomaly detection system — Part 2 Building ML Models with Observability at Scale By Rajeev Prabhakar , Han Wang , Anindya Saha Photo by Octavian Rosca on Unsplash In our previous blog we discussed the different challenges we faced for model monitoring and our strategy for addressing some of these problems.

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Systems Building Machine Learning Datasets 76

DataKitchen

DECEMBER 9, 2022

This can include the use of tools for data preparation, model training, and deployment, as well as technologies for monitoring and managing data-related systems and processes. One of the key benefits of DataOps observability is the ability to improve collaboration and communication across teams and systems.

Machine Learning 52

Machine Learning Data Preparation Government Data Analytics 52

LinkedIn Engineering

DECEMBER 6, 2022

With a reasonably sizable footprint of servers in data centers, LinkedIn is responsible for ensuring that these hosts are always on an operating system (OS) version deemed the ���latest and greatest��� for all intents and purposes. Any data modification can be isolated by this means.

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Systems Metadata Datasets Designing 55

Edureka

JULY 18, 2024

It understands concepts like ambiguity and nuance – the two biggest blindspots of traditional computer systems This shift from generic AI to context-aware systems paves the way for a more natural and effective human-machine interaction. Think about a smart home system. New to generative AI? How Does Contextual AI Work?

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Systems Retail Food Education 40

Data Engineering Weekly

JULY 7, 2024

The blog highlights the advantages of GNN over traditional machine learning models, which struggle to discern relationships between various entities, such as users and restaurants, and edges, such as order. Canva writes about the evolution of experimentation system design and the current state of the function.

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Data Science Blog: Data Engineering

SEPTEMBER 19, 2023

In the contemporary age of Big Data, Data Warehouse Systems and Data Science Analytics Infrastructures have become an essential component for organizations to store, analyze, and make data-driven decisions. Scalability Tailored for Data Needs Data Warehouse Systems often require to scale quickly to handle larger datasets or more queries.

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Netflix Tech

OCTOBER 8, 2024

In previous blog posts, we introduced the Key-Value Data Abstraction Layer and the Data Gateway Platform , both of which are integral to Netflix’s data architecture. Note: Contrary to what the name may suggest, this system is not built as a general-purpose time series database.

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ProjectPro

JANUARY 15, 2021

And honestly, there are a lot of real-world machine learning datasets around you that you can opt to start practicing your fundamental data science and machine learning skills, even without having to complete a comprehensive data science or machine learning course. Table of Contents What is a dataset in machine learning?

Machine Learning 40

Machine Learning Datasets Retail Banking 40

Cloudera

DECEMBER 7, 2020

Apache Hadoop Distributed File System (HDFS) is the most popular file system in the big data world. The Apache Hadoop File System interface has provided integration to many other popular storage systems like Apache Ozone, S3, Azure Data Lake Storage etc. Migrating file systems thus requires a metadata update. .

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Systems Hadoop Metadata Datasets 60

Data Engineering Weekly

SEPTEMBER 18, 2024

Storage and computing were tightly coupled within a single, large system, making running additional processes, such as observability tools, difficult without straining the system’s resources. It ensures you can trust the data flowing through your systems and react quickly to any issues.

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Data Lake Data Pipeline Unstructured Data Datasets 98

Cloudyard

NOVEMBER 17, 2024

With built-in and custom metrics, DMFs simplify the process of validating large datasets and identifying anomalies. In this blog, we will explore a practical use case of DMFs to monitor the quality of transactional data. Scalability : Handle large datasets without compromising performance.

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Datasets Data Government Data Validation 52

Knowledge Hut

FEBRUARY 29, 2024

Then, based on this information from the sample, defect or abnormality the rate for whole dataset is considered. Hypothesis testing is a part of inferential statistics which uses data from a sample to analyze results about whole dataset or population. It offers various blogs based on above mentioned technology in alphabetical order.

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Data Science Datasets Machine Learning Database Design 98

Data Engineering Weekly

JULY 28, 2024

The blog is an excellent summarization of the common patterns emerging in GenAI platforms. Switching from Apache Spark to Ray improves compact 12X larger datasets than Apache Spark, improves cost efficiency by 91%, and processes 13X more data per hour. Swiggy recently wrote about its internal platform, Hermes, a text-to-SQL solution.

Data Engineering 109

Data Engineering Data Engineer Engineering Database-centric 109

Pinterest Engineering

OCTOBER 11, 2024

In Part 2 of our blog series, we described how we were able to integrate Ray(™) into our existing ML infrastructure. In this blog post, we will discuss a second type of popular application of Ray(™) at Pinterest: offline batch inference of ML models. Dataset execution is pipelined so that multiple execution stages can run in parallel.

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Datasets Software Engineering Software Engineer Metadata 63

Data Engineering Weekly

AUGUST 6, 2024

CDC Evaluation Guide Google Sheet Link: [link] CDC Evaluation Guide Github Link: [link] Change Data Capture (CDC) is a powerful technology in data engineering that allows for continuously capturing changes (inserts, updates, and deletes) made to source systems. Impacts source system performance during query execution.

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Data Lake Data Warehouse Database Data Architecture 125

Cloudera

FEBRUARY 8, 2022

Cloudera has been recognized as a Visionary in 2021 Gartner® Magic Quadrant for Cloud Database Management Systems (DBMS) and for the first time, evaluated CDP Operational Database (COD) against the 12 critical capabilities for Operational Databases. Critical Capabilities for Cloud Database Management Systems for Operational Use Cases .

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Database Systems Cloud Management 66

Pinterest Engineering

JANUARY 4, 2024

In 2020, anticipating the growing needs of the business and to simplify our storage offerings, we decided to consolidate our different key-value systems in the company into a single unified service called KVStore. Maintaining these disparate systems and building common functionality among them was adding a huge overhead to the teams.

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Database Building Datasets Relational Database 93

Data Engineering Weekly

JULY 14, 2024

The blog highlights the reasoning behind selecting dbt and Dagster and some of the key improvements while adopting them, such as handling race conditions in dbt incremental update and bulk backfilling with Dagster. Metabase writes about why they build a continuous enrichment pipeline for customer contacts pipeline and its system design.

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Data Engineering Data Engineer Engineering Unstructured Data 98

Data Engineering Weekly

SEPTEMBER 29, 2024

Grab confirms my observation that users abandoned their searches in 18% of sessions without clicking on any dataset. This suggested that the search results were not meeting their needs, which led to redesigning the system to focus on search accessible where data consumers hang out the most: Slack.

Data Engineering 62

Data Engineering Data Engineer Engineering SQL 62

Cloudera

NOVEMBER 13, 2024

Fine Tuning Studio enables users to track the location of all datasets, models, and model adapters for training and evaluation. The goal is to fine tune a small, cost-effective model that , based on customer input, can extract an appropriate “action” (think API call) that the downstream system should take for the customer.

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Datasets Machine Learning Coding Data Preparation 60

Pinterest Engineering

SEPTEMBER 12, 2023

transformers) became standardized, ML engineers started to show a growing appetite to iterate on datasets. While such dataset iterations can yield significant gains, we observed that only a handful of such experiments were conducted and productionized in the last six months. As model architecture building blocks (e.g.

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Data Process Process Datasets Software Engineer 102

Pinterest Engineering

NOVEMBER 18, 2024

In this blog post, we’ll explore what CDC is, why it’s important, and our journey of implementing Generic CDC solutions for all online databases at Pinterest. This is crucial for applications that require up-to-date information, such as fraud detection systems or recommendation engines. What is Change Data Capture?

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Kafka MySQL Database Software Engineer 46

Data Engineering Weekly

SEPTEMBER 15, 2024

impactdatasummit.com Ravi Vedula: The evolution of a data platform - The story of the Microsoft IDEAS team Microsoft IDEAS (Insights, Data, Engineering, Analytics, Systems) team writes about the evolution of the data platform. Though the blog talks specifically to Beam, every pipeline can adopt the theme.

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Data Engineering Data Engineer Engineering Data Lake 67

Data Engineering Weekly

AUGUST 25, 2024

Google’s search ranking system is a complex, multi-step process that begins with indexing new content, assigning it a unique DocID, and calculating its relevance based on keyword presence. The blog is a good overview of various components in a typical data stack. This is a must-read for this week.

Data Engineering 70

Data Engineering Data Engineer Engineering Database-centric 70

Pinterest Engineering

SEPTEMBER 26, 2023

We have published a detailed blog post of its modeling architecture. The frontend logging system tracks the Pins that have been impressed by the Pinner and keeps a low percentage of the impressions and all positive engagements. The recommendations are powered by innovative and cutting-edge machine learning technologies.

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Software Engineer Software Engineering Machine Learning Datasets 103

Pinterest Engineering

JULY 25, 2023

Each dataset needs to be securely stored with minimal access granted to ensure they are used appropriately and can easily be located and disposed of when necessary. As businesses grow, so does the variety of these datasets and the complexity of their handling requirements.

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Big Data Accessible Accessibility Hadoop 98

Christophe Blefari

AUGUST 24, 2024

will feature: a new web UI, DAG versioning, remote execution (from cloud to on-prem), data assets (like Dagster, a renaming of Datasets) and more but that's a great milestone. LETSQL inference for DataFrames — I don't understand the blog but looks cool. If we look at the confluence page Airflow 3.0

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BI Food Data SQL 130

Workfall

JULY 18, 2023

As one of those wizards, we’ve seen the challenges we face: the struggle to transform massive datasets into meaningful insights, all while keeping queries fast and our system scalable. In this blog, we’ll whisk you away on an enchanting journey through DBT materializations. In this blog, we will cover: What is DBT?

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Datasets Entertainment Data Workflow Data 77

Christophe Blefari

JULY 13, 2024

AI News 🤖 OpenAI — Always the biggest news provider, announcements or dramas OpenAI was hacked, revealing internal secrets and raising national security concerns — The hacker reached OpenAI’s internal messaging systems early last year, stealing details of how OpenAI's technologies work from employees.

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Kafka AWS Data Database 130

Scott Logic

SEPTEMBER 13, 2024

In this blog, we will look at how ML has developed, how it might affect our job as test engineers and the important strategies, considerations and skills needed to effectively evaluate and test ML models. They are trained on large datasets to recognise patterns and make predictions or decisions based on new information.

Medical 52

Medical Hospitality Datasets Machine Learning 52

Databand.ai

AUGUST 30, 2023

The importance of data quality cannot be overstated, as poor-quality data can result in incorrect conclusions, inefficient operations, and a lack of trust in the information provided by a company’s systems. Consistency: The uniformity of data across different sources or systems.

Data Cleanse 52

Data Cleanse Metadata High Quality Data Datasets 52

Edureka

OCTOBER 10, 2024

Another element that can be identified in both services is the copy operation, with the help of which data can be transferred between different systems and formats. In this all-encompassing tutorial blog, we are going to give a detailed explanation of the Copy activity with special attention to datastores, file type, and options.

MongoDB 40

MongoDB NoSQL Metadata Datasets 40

DataKitchen

MAY 10, 2024

This blog post introduces five critical use cases for data observability, each pivotal in maintaining the integrity and usability of data throughout its journey in any enterprise. Production During the production cycle, it’s crucial to oversee processes involving multiple tools and datasets, such as dashboard production or warehouse building.

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Data Ingestion Datasets Data Coding 57

DataKitchen

NOVEMBER 5, 2024

This foundational layer is a repository for various data types, from transaction logs and sensor data to social media feeds and system logs. The Medallion architecture is a framework that allows data engineers to build organized and analysis-ready datasets in a lakehouse environment. How do you ensure data quality in every layer?

Architecture 79

Architecture Raw Data Pipeline-centric Data Ingestion 79

Pinterest Engineering

MAY 2, 2023

So our user sequence real-time indexing pipeline is composed of a Flink job that reads the relevant events as they come into our Kafka streams, fetches the desired features for each event from our feature services, and stores the enriched events into our KV store system. We need each dataset to store the last N events for a user.

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Lambda Architecture Datasets Software Engineering Software Engineer 80

Data Science Blog: Data Engineering

AUGUST 22, 2024

If you input poor-quality data into an AI system, the results will be poor. Tools like BiG EVAL are leading data quality field for all technical systems in which data is transported and transformed. The post Looking Ahead: The Future of Data Preparation for Generative AI appeared first on Data Science Blog (English only).

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Data Preparation Transportation High Quality Data Data Science 52